Abstract: Using the syntactic analysis model, the statement is divided into several combinations of words. According to the subject-predicate component of compound words and emotional color difference of emotional words, different weights are given respectively. The authors statistically analyze the distribution of the emotional statement, use the characteristic parameter training the classifier, and employ the trained classifier for the test corpus emotional classification. Experiment results show that the emotion classification discriminant accuracy rate and recall rate of this method is more ideal, compared with the existing discrimination methods. This method can also be used in the statement of comparative discrimination and negative polarity judgment.

Key words: cross-language, sentiment analysis, parser, Bayes classification

摘要： 利用句法分析模型, 将语句分成若干组合词, 根据组合词的主谓成分中情感词对于句子情感贡献的不同, 分别赋予不同的权重。统计分析该语句的情感分布特征, 利用得到的特征参数训练分类器, 再将训练好的分类器用于测试语料的情感分类。实验结果表明, 与已有的判别方法相比, 该方法的情感分类判别准确率较理想。此方法也可用于语句的比较级判别和否定句的极性判断等。

关键词: 跨语言, 情感分类, 句法分析, 贝叶斯分类